Search results for "TJ"
showing 10 items of 841 documents
On resampling schemes for particle filters with weakly informative observations
2022
We consider particle filters with weakly informative observations (or `potentials') relative to the latent state dynamics. The particular focus of this work is on particle filters to approximate time-discretisations of continuous-time Feynman--Kac path integral models -- a scenario that naturally arises when addressing filtering and smoothing problems in continuous time -- but our findings are indicative about weakly informative settings beyond this context too. We study the performance of different resampling schemes, such as systematic resampling, SSP (Srinivasan sampling process) and stratified resampling, as the time-discretisation becomes finer and also identify their continuous-time l…
Conditional particle filters with diffuse initial distributions
2020
Conditional particle filters (CPFs) are powerful smoothing algorithms for general nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult to apply with diffuse initial distributions, which are common in statistical applications. We propose a simple but generally applicable auxiliary variable method, which can be used together with the CPF in order to perform efficient inference with diffuse initial distributions. The method only requires simulatable Markov transitions that are reversible with respect to the initial distribution, which can be improper. We focus in particular on random-walk type transitions which are reversible with respect to a uniform init…
Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions
2021
We develop a Bayesian inference method for diffusions observed discretely and with noise, which is free of discretisation bias. Unlike existing unbiased inference methods, our method does not rely on exact simulation techniques. Instead, our method uses standard time-discretised approximations of diffusions, such as the Euler--Maruyama scheme. Our approach is based on particle marginal Metropolis--Hastings, a particle filter, randomised multilevel Monte Carlo, and importance sampling type correction of approximate Markov chain Monte Carlo. The resulting estimator leads to inference without a bias from the time-discretisation as the number of Markov chain iterations increases. We give conver…
Efficient Bayesian generalized linear models with time-varying coefficients : The walker package in R
2020
The R package walker extends standard Bayesian general linear models to the case where the effects of the explanatory variables can vary in time. This allows, for example, to model the effects of interventions such as changes in tax policy which gradually increases their effect over time. The Markov chain Monte Carlo algorithms powering the Bayesian inference are based on Hamiltonian Monte Carlo provided by Stan software, using a state space representation of the model to marginalise over the regression coefficients for efficient low-dimensional sampling.
The Max-Product Algorithm Viewed as Linear Data-Fusion: A Distributed Detection Scenario
2019
In this paper, we disclose the statistical behavior of the max-product algorithm configured to solve a maximum a posteriori (MAP) estimation problem in a network of distributed agents. Specifically, we first build a distributed hypothesis test conducted by a max-product iteration over a binary-valued pairwise Markov random field and show that the decision variables obtained are linear combinations of the local log-likelihood ratios observed in the network. Then, we use these linear combinations to formulate the system performance in terms of the false-alarm and detection probabilities. Our findings indicate that, in the hypothesis test concerned, the optimal performance of the max-product a…
Good Old-Fashioned Artificial Consciousness and the Intermediate Level Fallacy
2018
Recently, there has been considerable interest and effort to the possibility to design and implement conscious robots, i.e., the chance that a robot may have subjective experiences. However, typical approaches as the global workspace, information integration, enaction, cognitive mechanisms, embodiment, i.e., the Good Old-Fashioned Artificial Consciousness, henceforth, GOFAC, share the same conceptual framework. In this paper, we discuss GOFAC's basic tenets and their implication for AI and Robotics. In particular, we point out the intermediate level fallacy as the central issue affecting GOFAC. Finally, we outline a possible alternative conceptual framework towards robot consciousness.
Binder and Mixture Fatigue Performance of Plant-Produced Road Surface Course Asphalt Mixtures with High Contents of Reclaimed Asphalt
2019
The aged properties of Reclaimed Asphalt (RA) binders are one of the main factors working against their utilisation in high-RA content (>
Projekts: Šķeldas tirdzniecības uzņēmuma izveidošana
2016
Šī maģistra darbs ir izstrādāts projekta veidā, un tā nosaukums ir „Šķeldas tirdzniecības uzņēmuma izveidošana” (turpmāk tekstā – Projekts). Projekta pamatā ir autora vēlme izmantot savas iegūtās zināšanas un pieredzi, un iesaistīties tādu Latvijas tautsaimniecībai svarīgu problēmu risināšanā, kā Latvijas enerģētiskā neatkarība, enerģijas piegāžu drošums, efektivitāte un ilgtspējība, vides aizsardzība un siltumnīcefekta mazināšana, Latvijas reģionu konkurētspējas paaugstināšana. Autors nolēmis minēto problēmu risināšanā iesaistīties, Latvijas reģionā dibinot atjaunojamās enerģijas izejvielu piegādes uzņēmumu, par kura nepieciešamību, potenciālo darbību, rezultātiem un iespējamajiem problēmj…
Projekts: Vēja elektroenerģijas ražošanas uzņēmuma AS "Vēja resursi" dibināšana
2019
Pirmie vēja ģeneratori Latvijā tika uzstādīti 1995. gadā, kaut gan vēsturiski vēju enerģiju kā resursu sāka izmantot vēl aptuveni septiņus tūkstošus gadus atpakaļ. Šobrīd atjaunojamo energoresursu (AER), tajā skaitā arī vēja enerģijas, tēma ir ļoti aktuāla gan vides, gan enerģētikas, gan arī investīciju un biznesa jautājumu kontekstā, tāpēc AER tehniskā un politiskā attīstība ir ārkārtīgi strauja un darbības vide ļoti mainīga. 2009. gadā Eiropas Savienībā (ES) tika ieviesta atjaunojamo energoresursu direktīva (2009/28/EK)- vispārēja politiku, kas nosaka, ka līdz 2020. gadam vismaz 20% no kopējām ES enerģijas vajadzībām jānodrošina ar atjaunojamiem energoresursiem. Saskaņā ar Direktīvu Latvi…
Reputation-Based Blockchain for Spatial Crowdsourcing in Vehicular Networks
2022
The sharing of high-quality traffic information plays a crucial role in enhancing the driving experience and safety performance for vehicular networks, especially in the development of electric vehicles (EVs). The crowdsourcing-based real-time navigation of charging piles is characterized by low delay and high accuracy. However, due to the lack of an effective incentive mechanism and the resource-consuming bottleneck of sharing real-time road conditions, methods to recruit or motivate more EVs to provide high-quality information gathering has attracted considerable interest. In this paper, we first introduce a blockchain platform, where EVs act as the blockchain nodes, and a reputation-base…